The Child Emotion Facial Expression Set: A Database for Emotion Recognition in Children

Negrão, Juliana Gioia; Osório, Ana Alexandra Caldas; Siciliano, Rinaldo Focaccia; Lederman, Vivian Renne Gerber; Kozasa, Elisa Harumi; D'Antino, Maria Eloisa Famá; Tamborim, Anderson; Santos, Vítor; Leucas, David Leonardo Barsand de; Camargo, Paulo Sergio; Mograbi, Daniel C.; Mecca, Tatiana Pontrelli; Schwartzman, José Salomão

doi:10.3389/fpsyg.2021.666245

Cited by 21 publications

(4 citation statements)

References 32 publications

(57 reference statements)

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“…Состояние радости взрослые лучше определяют по фотографиям типично развивающихся детей 2-8 лет, по сравнению с гневом, страхом, печалью, удивлением и отвращением [19]. В другом исследовании по фотографиям и видеороликам типично развивающихся детей 4-6 лет специалисты в области кодирования действий по лицу с существенной согласованностью (коэффициент Каппа -0,70) определяли счастье, отвращение и презрение [34]. Дети, участвующие в этом исследовании, были отобраны в детском актерском агентстве в городе Сан-Паулу, Бразилия.…”

Section: Discussionunclassified

Recognition of Emotional States of Children with down Syndrome by Facial Expression: Perceptual and Automatic Analysis of Dynamic Images

Lyakso

Frolova

Grigorev

et al. 2022

Experimental Psychology (Russia)

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The study is devoted to the investigation of the recognition of the emotional state of children with Down syndrome (DS) by their facial expression. For this purpose, a series of perceptual experiments involving adults (n=75) and automatic analysis of the facial expressions of children (n=35, aged 5—16 years) were carried out using the FaceReader program. The ability of adults to recognize the emotional states of children: joy — neutral (calm state) — sadness — anger, by open faces and faces with masks over the eyes and mouth is shown. Better recognition of the state of joy and neutral state under the condition of an open face and a decrease in recognition accuracy in a mask in the eye area compared to the absence of a mask and a mask in the mouth area were found. Automatic recognition of the states of joy and neutral states is better than the states of sadness and anger, if the face is open and the mask in the mouth area of the child. The conditions for use the automatic recognition of facial expression in children with DS and for applying the method of perceptual analysis for identifying the specificity of the child emotional sphere development are discussed.

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Section: Discussionunclassified

Recognition of Emotional States of Children with down Syndrome by Facial Expression: Perceptual and Automatic Analysis of Dynamic Images

Lyakso

Frolova

Grigorev

et al. 2022

Experimental Psychology (Russia)

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“…In this study, the film was the chosen method for eliciting emotions. It was taken into consideration in this study that watching audiovisual stimuli evokes real emotions; thus, it generates more ecological stimuli ( Negrão et al, 2021 ). In psychology, an ecological stimulus is a measure of how test performance predicts behaviors in real-world settings.…”

Section: Discussionmentioning

confidence: 99%

Baseline emotional state influences on the response to animated short films: A randomized online experiment

et al. 2022

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IntroductionConsidering the relevance of the emotional state, it is necessary to understand how daily stimuli can modulate the emotions. Animated short films are common stimuli, but it is unknown how they can modulate the emotional state. The study aimed to evaluate: how participants’ emotional state changed after watching animated short films with positive or negative emotional valence in an online experiment; the relationship between participants’ baseline score on an Emotional Intensity Scale and their potential change in the main emotion after watching the films; and the association between the initial main emotion valence and the potential change in this emotion with participants’ sociodemographic information.MethodsA sample of 2,269 participants recruited during COVID-19 pandemic were randomly assigned to either watch a negative or positive animated short film.ResultsThe results showed that, after watching a film with negative valence, participants were in a more negative emotional state than at baseline and compared with those who watched the film with positive valence. Also, individuals who had a negative baseline emotion and maintained the same emotion after the film had presented higher baseline emotional state scores (more negative emotion) than those who changed their emotions. In addition, the individuals who kept the baseline emotion had an association with age, marital status, level of education and psychiatric disorders, use of medication, and emotional awareness, while the individuals who changed the baseline emotion had an association with age, gender, and following or not social distancing recommendations.ConclusionBaseline emotional state may influence the response to animated short films and sociodemographic characteristics are associated with the initial main emotion valence and its potential change in this emotion.

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“…Participants were involved in video and image shoots intended to evoke certain emotions, and the resulting photos were then judged in two rounds by impartial judges. For each emotion, there were 87 stimuli for neutrality, 363 stimuli for joy, 170 stimuli for disgust, 104 stimuli for surprise, 152 stimuli for fear, 144 stimuli for sadness, 157 stimuli for anger, and 183 stimuli for contempt [3].…”

Section: Sample Dataset Images (City Infant Faces Database)mentioning

confidence: 99%

Application of Machine and Deep Learning Techniques to Facial Emotion Recognition in Infants

Pandyan¹,

Sindha²,

Kannapiran³

et al. 2023

Emotion Recognition - Recent Advances, New Perspectives and Applications

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Infant facial expression recognition is one of the most significant areas of research in the field of computer vision and surveillance parental care. It is essential for both the early diagnosis of medical conditions and intelligent interpersonal interactions. Despite recent improvements in face detection, feature extraction techniques, and expression categorization methods, it is still difficult to develop an automated system employing deep learning methods that achieves the goal of recognizing infant emotions. The prime aim of this chapter is to present a comprehensive framework for recognizing infant emotions using machine learning and deep learning algorithms on the dataset for infant emotions currently accessible. The proposed model directs future research on early detection of infant emotions and has the ability to identify emotional-related medical problems. This article will incorporate the findings on infant emotion recognition required to address the parental supervision and enhance intelligent interpersonal relationships.

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The Child Emotion Facial Expression Set: A Database for Emotion Recognition in Children

Cited by 21 publications

References 32 publications

Recognition of Emotional States of Children with down Syndrome by Facial Expression: Perceptual and Automatic Analysis of Dynamic Images

Recognition of Emotional States of Children with down Syndrome by Facial Expression: Perceptual and Automatic Analysis of Dynamic Images

Baseline emotional state influences on the response to animated short films: A randomized online experiment

Application of Machine and Deep Learning Techniques to Facial Emotion Recognition in Infants

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